Itzik Ben-Gan dissects the Hash Match (Aggregate) algorithm in his latest post in a series on SQL Server optimization thresholds.
Articles by SQLPerformance.com
Tim Radney goes into detail about why baselines are important, and how metrics you collect now can help you solve future problems.
Continuing his series on optimization thresholds, Itzik Ben-Gan dives into the costs behind stream aggregates when the data needs to be sorted first.
Glenn Berry discusses a number of compelling reasons why, if you are choosing between SQL Server 2016 or SQL Server 2017, you should choose the newer version.
For his first post on SQLPerformance.com, Itzik Ben-Gan shows you how to reverse engineer optimizer costing for a Stream Aggregate operator.
Following up on her post about automatic plan correction, Erin Stellato talks about a new feature in Azure SQL Database: Automatic Index Management.
Rob Farley describes a tactic where adding multiple predicates around separate date and time columns can win you some better performance.
Paul White continues his series on row goals, treating a redundant and problematic TOP (1) that is added to the inner side of an apply anti join.
Usually DISTINCT and GROUP BY will yield the same results, but here Rob Farley explains cases that can break the rule.
Continuing his in-depth series on row goals, Paul White explains both why and how they can impact queries involving anti joins.
Glenn Berry explains how the Spectre/Meltdown issues (and their patches!) may affect SQL Server performance, and provides a handy list of mitigation steps to keep your servers protected.
Continuing his series on row goals, Paul White explains how they can impact certain types of semi joins, and how you can spot these effects in showplan and trace flag output.
Erin Stellato gives an overview of Automatic Plan Correction in SQL Server 2017 and Azure SQL Database, and assures us that Microsoft is not trying to code us out of jobs.
Paul White provides some great information about row goals, explaining why they're important to understand when examining why the query optimizer made a certain choice.
Aaron Bertrand addresses the questions raised during two parameter sniffing webinars in January with Kimberly L. Tripp and Andy Mallon.
